Analyzing Peptide Microarray Data with the R pepStat Package

Methods Mol Biol. 2016:1352:127-42. doi: 10.1007/978-1-4939-3037-1_10.


In this chapter we demonstrate the use of R Bioconductor packages pepStat and Pviz on a set of paired peptide microarrays generated from vaccine trial data. Data import, background correction, normalization, and summarization techniques are presented. We introduce a sliding mean method for amplifying signal and reducing noise in the data, and show the value of gathering paired samples from subjects. Useful visual summaries are presented, and we introduce a simple method for setting a decision rule for subject/peptide responses that can be used with a set of control peptides or placebo subjects.

Keywords: Background correction; Baseline correction; Data visualization; Decision rule; False discovery rate; Normalization; Sliding mean; Smoothing.

MeSH terms

  • Antibodies / immunology
  • Clinical Trials as Topic
  • Humans
  • Peptides / immunology
  • Peptides / metabolism*
  • Protein Array Analysis / methods*
  • Statistics as Topic / methods*
  • Vaccines / immunology


  • Antibodies
  • Peptides
  • Vaccines